Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Mitigation of Train-Induced waves by resonant filled-trench (RFT)

The increase of railways near the urban areas is a significant cause of discomfort for inhabitants due to train-induced vibration and noise. Vibration characteristics can vary widely according to the train type: for high-speed trains, if train speed becomes comparable to the ground wave speed, the vibration level becomes significant; for freight trains, due to their heavier weight and lower speed, the vibration amplitudes are greater and propagate at a more considerable distance from the track; for urban tramways, although the vibration amplitude is relatively low, they can have a negative structural effect on the closest buildings [51]. Therefore, to dampen the vibration level, it is possible to carry out some interventions both on the track and the transmission path. This thesis aims to propose and numerically investigate a novel method to dampen the train-induced vibrations along the transmission path. The method is called "resonant filled-trench (RFT)" and consists of a combination of expanded polystyrene (EPS) geofoam to stabilize the trench wall against the collapse and drowned cylindrical embedded inclusions inside the geofoam, which act as a resonator, reflector, and attenuator. By means of finite element simulations, we show that up to 50% higher attenuation than the open trench is achievable after overcoming the resonance frequency of the inclusion, i.e., 35Hz, which covers the frequency contents of the train-induced vibration. Moreover, depending on the filling material used for the inclusions, trench depth can be reduced up to 17% compared to the open trench showing the same screening performance as the open trench. Also, an RFT with DS inclusion installed in dense sand soil shows a high hindrance performance (i.e., IL≥6dB) when the trench depth is larger than 0.5λ_R while it is 0.6λ_R for the open trench.